When a person speaks in presence of background noise he or she, in many cases unconsciously, adjusts the way he/she is speaking due to the background noise. The adjustment most notably comprises adjusting of voice loudness, but also adjustment of intonation, speaking pace and/or the spectral content etc. may be observed as a result of the speaker trying to adapt his/her voice to be heard better in presence of the background noise. This adjustment or adaptation is based on the auditory feedback from his/her own voice and the background noise—and interaction of the two. Such an adjustment of voice by the speaker may be referred to as a secondary impact of the background noise.
Many voice capturing arrangements apply noise suppression in order to remove/cancel or at least substantially reduce the background noise in the captured signal. However, while noise suppression is applied, the resulting speech from which the noise is removed or reduces still remains “adjusted” to the environmental background noise. This may make the resulting speech to sound unnatural, annoying and/or even disturbing once the background noise has been removed or reduced, possibly even reducing the intelligibility of the speech. The impact may be especially disturbing for the listener when the characteristics of background noise change rapidly during talking e.g. when during a phone call the far-end speaker raises his/her voice loudness temporarily due to environmental noise, e.g. due to traffic noise caused by a car passing by. Typically, the better the noise suppression is the more noticeable and disturbing this effect may be. Moreover, with possible upcoming advances in noise suppression techniques this issue can be expected to become even more prominent.
Enhancement of a speech signal in the presence of background noise is widely researched topic, having resulted in techniques such as noise cancelling, adaptive equalization, multi-microphone systems etc. aiming to either reduce the background noise in the captured signal or to improve the actual capture so that it becomes less sensitive to background noise. However, such speech enhancement techniques fail to address the above-mentioned issue of the speaker adapting his/her voice in presence of background noise.